Mobile sensor can be used to acquire images in a coordinated manner. The images can then be used in applications such as surveilance, cartography, and environmental monitoring. One problem in such systems is planning the paths the sensors should follow, a problem known as path planning.
In one such system with holonomic robots, where the controllable degrees of freedom are equal to the total degrees of freedom, anisotropic sensors with a bounded footprint are considered, see Hexsel et al., “Distributed Coverage Control for Mobile Anisotropic Sensor Networks,” Tech. Report CMU-RI-TR-13-01, Robotics Institute, Carnegie Mellon University, January 2013. That system models a 2-dimensional (2D) environment as a polygon, possibly containing obstacles. A fixed objective function maximizes a joint probability to detect objects. The objective function uses an a priori fixed density function that represents an importance of each point in the environment.